Student assistant: »Physics-based machine learning for process optimization in machining domain«

The Fraunhofer-Gesellschaft (www.fraunhofer.com) currently operates 76 institutes and research institutions throughout Germany and is the world’s leading applied research organization. Around 30,800 employees work with an annual research budget of 3.0 billion euros.

The »High Performance Cutting« department develops technologies and application-oriented solutions for machining along the entire process chain – from process design to real-time data acquisition for generating a digital twin during production to consulting and prototype production. Physics based ML approach to detect vibrations from sensor data that are detrimental to surface quality can act as a powerful tool to optimize the cutting process. Implementation of ML algorithms in various other use cases could also speed up processes and increase the accuracy of the digital twin model developed at Fraunhofer IPT.

What you will do

• Collaboration in current research and industrial projects with special focus on implementation of ML algorithms
• Investigate utilization of graph neural networks (GNN) and physics-based ML approach in the domain of dynamic stability of machining process
• Software development with microservice architecture in cloud environment for the machining domain

What you bring to the table

• You are studying Computer science, Mechatronics, Mechanical Engineering or a comparable subject
• First Experience in programming (e.g., Python or C++) are desirable
• Practical core knowledge of ML approaches would be advantageous
• A high degree of initiative, motivation and team spirit

What you can expect

• A state-of-the-art machine park equipped with edge cloud systems and 5G infrastructure
• Collaboration in innovative research projects and the chance to implement your knowledge from your studies in practice
• Flexible working and trust to drive tasks at your own responsibility
  The opportunity to write your practice-oriented thesis with us

Interested? Apply online now. We look forward to getting to know you!

https://jobs.fraunhofer.de/job-invite/73266/

For any further information on this position please contact:
Aakash Singh M.Sc.
Research assistant »High Performance Cutting«
Phone: +49 241 8904-587